Staff Research Scientist, Dexterous Manipulation

Your New Role and Team

Sanctuary, a world leader in building AI-based control systems for humanoid robots, is seeking a Staff Research Scientist to join our team in engineering and innovating unique robotic manipulation tasks.

As a Staff Research Scientist, your role will involve choosing the most cutting-edge methods, creating training and data collection systems, overseeing the evaluation of these algorithms in simulated environments, and implementing them on our robots in real-world situations. You will also enjoy the exclusive chance to make a meaningful impact by working with novel haptic and proprioceptive sensing techniques, thanks to our in-house robot with dexterous hands.

Success Criteria

• Create, develop, and enhance cutting-edge Reinforcement Learning (RL) and Imitation Learning (IL) algorithms and evaluate their performance in practical applications

• Stay current with the latest developments in RL/IL techniques and their application in robotics

• Identify, communicate, and lead research initiatives that show promise to the wider ML team

• Discover strategies for enhancing current RL/IL learning processes, considering key performance metrics like sample efficiency, speed, computational resources, and scalability

• Devise RL/IL training and data collection pipelines to expedite implementation on physical robots

• Collaborate within a diverse team to devise innovative algorithms and investigate the root causes of errors in existing implementations

Your Experience

Qualifications

• Ph.D. in Machine Learning, Computer Science, Applied Mathematics, or equivalent practical background in Reinforcement Learning and/or Imitation Learning

• 5+ years of hands-on experience implementing and deploying robotic manipulation tasks, both in simulation and on physical robots

• 5+ years of practical experience applying various Reinforcement Learning and/or Imitation Learning methods, with focus on robotics in the real world

• 4+ years experience in developing and optimizing large-batch parallel simulations for Reinforcement Learning

• Proven expertise in continual learning, employing adaptive model training to improve long-term performance and accuracy

• Proven expertise in sim-to-real transfer

• Experience in transitioning Machine Learning research and trained models into real-world production

• Active involvement in integrating Machine Learning models into a robotics platform

• A track record of publishing research in esteemed AI conferences such as ICRA, IROS and CORL

Skills

• Development with Python 3.8 or later

• Working knowledge of PyTorch and/or TensorFlow

• Familiarity with ROS2

• Expertise in use of Reinforcement Learning principles and their application

• Experience with Atlassian tools; Jira, Confluence, or equivalent i.e. GitLab

Traits

• Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems

• Strong leadership skills in organizing R&D work for ML projects

• Eager to take on new challenges with tenacity and positivity

• Patience, persistence, and attention to detail when resolving performance issues

• Enthusiasm for bringing human-like intelligence to machines

• Ability to drive development of new functionalities from concept to production

• Ability to multitask and prioritize in a fast paced environment